A Framework to Profile Your Ideal Customer

In our last blog post, we focused on why it is critical for your B2B business to spend time understanding your ideal customer profile. In this article, we will begin to construct a framework for how you can go about doing it.

The two pillars that are necessary to build this framework are B2B data and insights about the needs of your potential customers. Both are necessary, and they complement each other. However, it is important to understand the difference between each, as well as the often misunderstood difference between correlation and causation.

An excellent example to help understand the interplay of these key elements is described by Clayton Christensen, David Duncan, Karen Dillon, and Taddy Hall in their book, “Competing Against Luck.” They give the example of a fast food company that wanted to improve its sales of milkshakes. After having discussions and trying experiments along various dimensions that resulted in no improvement in sales whatsoever, they asked a researcher to gather detailed information on all milkshake sales, including when each milkshake was bought, whether the customer was alone or in a group, what other products were also purchased, and so on. To the researcher’s surprise, he noted that almost 40% of milkshake sales occurred early in the morning as a takeout order by people traveling alone. This data prompted the researcher to interview these early morning customers to ask why they bought a milkshake (and nothing else) at this particular time of the day.

What he gained from these interviews were fascinating insights. He found that most of these customers had a long, boring commute and needed something to make their drive more interesting. The commuters knew they weren’t yet hungry enough to want a full meal, but they might need enough to get them through a 10 a.m. dip and stave off hunger until noon. They also faced constraints: They were in a hurry, they were wearing work clothes, and they had only one free hand. A milkshake was a good solution because it was easy to carry (fit in the cup-holder), could be sipped a little at a time with one hand for twenty minutes (addressing the boredom issue), and was substantial enough to carry them through the potential 10 am hunger window until noon.

Having these valuable insights allowed the company to take steps that would better meet the needs of these customers, such as making the shakes thicker so they would last longer on the drive, and moving a milkshake dispensing machine in front of the counter and selling customers a prepaid swipe card so they could rush in, “load up,” and go off on their drive without having to wait in line with the other customers.

This example shows how data (the researcher seeing notable trends that could then direct the best questions to ask in interviews) combined with insights (resulting from the one on one interviews) led to a much better profiling of customers and a deeper understanding of their needs. By better addressing these needs, the company was able to significantly increase sales.

The fast food company is an example of a B2C business using data and insights to better understand its ideal customer profile that we like because it clearly illustrates how all these pieces interact. In the case of B2B businesses, we use the same general principles but there are additional dimensions to consider, which we will explore in future posts.

I have sold multi-million dollar enterprise deals to some of the largest companies in the world; managed high volume transactional SaaS teams, developed & managed channel strategies / partners, sold internationally and been through a couple acquisitions. I have not “seen and done it all”, but I have done quite a few things.